0181fe9fc837b8cdcc612375f2f174c5652ef87a,example/mpii.py,,validate,#Any#Any#Any#Any#Any#,194

Before Change

        // generate predictions
        preds = final_preds(output[-1].data.cpu(), meta["center"], meta["scale"], [64, 64])
        for n in range(output[-1].size(0)):
            predictions[meta["index"][n], :, :] = preds[n, :, :]

After Change

        loss = 0
        for o in output:
            loss += criterion(o, target_var)
        acc = accuracy(score_map.cuda(), target, idx)

        // generate predictions
        preds = final_preds(score_map, meta["center"], meta["scale"], [64, 64])
        for n in range(score_map.size(0)):

Instances